The recent proliferation of "omics" (genomic, transcriptomic, proteomic, and metabolic) data has necessitated a parallel expansion in the field of systems biology to meet the rising demands for analyzing this abundance of data. Constraints-based modeling, which has proven quite successful in recent years, is an approach whereby the allowable cellular phenotypes are calculated by elimination of infeasible behaviors through the successive imposition of constraints (stoichiometric, thermodynamic and flux capacity constraints). The R01 funding program begun in 1998 has enabled us to: 1) develop genome-scale constraints-based metabolic models for E. coli, S. cerevisiae, H. influenzae, and H. pytori; 2) develop methods to analyze these metabolic networks; 3) develop methods for modeling regulation, including building a core regulatory model for E. coli; and 4) develop methods for the sequenced-based analysis of metabolic demands for transcription and translation. The proposed work presented here will build on our previous accomplishments. We propose to:1.) Expand our E. coli metabolic model to include more E. coli metabolic gene products as they become characterized, and to expand our E. coli regulatory and transcription and translation models to genome-scale. II) Integrate these three components, resulting in a comprehensive model describing metabolism, regulation, transcription, and translation and will account for roughly 2000 of the 4,401 open reading frames found in E. coli K-12 MG1655. This integrated model will then be used to develop a data-driven model-centric database, where "omics" data can place additional constraints on the allowable solution space and can be used to calculate biological parameters. The database will also provide predictions in silico of transcriptomic, proteomic, metabolomic, and phenomic data for prospective experimental design. if the proposed program is approved and implemented, we will construct and test the most comprehensive single cell model ever. This in silico model should serve as a basis for generating highly focused hypotheses and should be extendable to other sequenced strains of E. coli.